Triple
T8331701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One Day in the Life of Ivan Denisovich |
E195087
|
entity |
| Predicate | censorshipStatusAtPublication |
P40618
|
FINISHED |
| Object | officially approved |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: officially approved | Statement: [One Day in the Life of Ivan Denisovich, censorshipStatusAtPublication, officially approved]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: censorshipStatusAtPublication Context triple: [One Day in the Life of Ivan Denisovich, censorshipStatusAtPublication, officially approved]
-
A.
censorshipStatusAtTime
chosen
Indicates the censorship status of something at a specific point in time, capturing whether and how it was censored then.
-
B.
revisedVersionCensorshipStatus
Indicates the censorship or restriction status applied to a revised version of some original content.
-
C.
censorshipStatusChange
Indicates a change in an entity’s censorship state, such as being newly censored, uncensored, or having its censorship level modified.
-
D.
censorshipLevel
Indicates the degree or strictness of control, suppression, or restriction applied to information, media, or expression.
-
E.
censorshipYear
Indicates the year in which an act of censorship was imposed on the referenced content or entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca82e87f2c8190bdb71ee29dfc642d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7fbb2a3881909ef09ffcfcbb6e77 |
completed | March 31, 2026, 8:03 a.m. |
| PD | Predicate disambiguation | batch_69cb70c3231c81909e3d463192c9de22 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:56 p.m.